Roughly 80 percent of Americans shop online today, compared to approximately 46 percent who did in the year 2000. Based on those rising numbers and recent headlines, it’s easy to assume that brick-and-mortar retailing is sliding toward obsolescence. But the facts don’t agree. In 2017, 42 percent of large retailers grew their number of brick and mortar stores, while only 15 percent experienced a net decrease. Quarter over quarter, the retail sector is increasing its revenues and profits.

This map of the San Francisco Bay Area in California displays buyer analysis representing the average spend per customer neighborhood, regardless of where they shop, or if online. Dark green is highest. This is part of the equation for stores when planning merchandise mix and/or locations for stores.

Esri

The key to retail success, then, isn’t pitting one shopping format against another; it’s unifying them all. In an era of unified commerce, this means retailers looking to maintain or grow market share must predict where and how their customers will be buying, and seamlessly deliver online and in-store experiences for them. However, these experiences can’t be mass produced—today’s buyers want personalized interaction. And the key to delivering these tailored experiences lies in understanding and catering to distinct buying personas.

By tailoring the end-to-end shopping experience to the desires of specific consumer segments, retailers are becoming more competitive and capturing a larger share of wallet. So how do they identify where and how to serve their customers—particularly the most valuable ones?

Customer Analytics

To attract and keep customers, retailers need to understand them, and not just at a market level. Location intelligence, which is enriched by spatial analytics, helps retailers identify specific customer segments by finding deeper insight into customer data. This includes knowledge not just about what ZIP code customers live in or how far they live or work from stores, but valuable geographic insights such as neighborhood age groups, average earnings, buying power, education levels, and professional status.

This map displays where people shop in the San Francisco Bay Area. Those in green shop in downtown San Francisco, where they work, as opposed to where they live.

Esri

Top retailers translate that information into distinct localized segment demographics, which can be analyzed to create a reusable index of the highest performing buying behaviors. Those buying behaviors are also known as the customers’ “path-to-purchase,” the cycle of decision-making from demand to buying. Members of a customer segment tend to follow a similar path-to-purchase. They also tend to live, work and play in very similar places—something retailers can discover using location intelligence.

One retailer that came to market offering discount beauty products has outperformed its competitors by using location intelligence to better understand its highest performing customer segments. The company didn’t simply open more stores, deepen discounts, or offer free shipping. Its executives used location intelligence to understand the needs of certain customer segments in various geographic locations, and then designed personalized experiences both in-store and online. That included catering to some of the most profitable segments with in-store salons and hands-on product testing, as well as complimentary online products and resources.

In essence, the retailer used location intelligence to understand that some customers want more than just a store where they can buy beauty products at a low price. Instead, certain segments want what the CEO calls a beauty destination. In part because of these enhancements, the business has grown sevenfold in only a few years in a highly competitive market.

In the age of unified commerce and the empowered consumer, retailers must now deliver a seamless experience across digital and physical locations. Most consumers expect to combine those experience holistically—even using their mobile devices while in the store to compare prices, redeem real-time coupons and make purchases. Savvy retailers can learn even more about their buyers from this digital footprint, including in-store foot traffic patterns and average times spent in store—by season, day of week, even down to time of day and purchasing patterns. All of this data provides the next level of spatial analysis that helps retailers strengthen customer segment analytics and personalize the shopping experience with greater precision.

Localization

Localization is a capability which allows retailers to tailor stores, websites and merchandise to the expectations of well-defined customer segments, ensuring that those customers will be more satisfied, post better reviews and more likely to return.

One national general merchandise discount retailer with more than 14,000 stores and big expansion plans has become expert at personalizing its store experience with the help of location intelligence. Unlike most big box retailers, this business focuses on location-specific performance indicators, rather than a monolithic, chain-wide strategy. While the company’s sales are primarily made in-store, they are supported by a tailored online experience based on the shopper’s location. This enables customers to price compare, download digital coupons, and create a digital shopping cart for his or her local store.

In this case, the retailer’s success is directly connected to knowing its core buyer segment—shoppers looking for affordable, everyday household products in a clutter-free store. Within that core segment, the retailer customizes each store’s product mix and pricing based on the demographic attributes of the shoppers in that area.

Retail’s Spatial Advantage

The reality of retail today is that the buyer is empowered with technology and information. Customers can get almost anything they want, anywhere, at any time. But more than convenience and discounts, what they’re seeking is a tailored, made-to-order buying experience.

The advantage lies with the firms that can adjust their business models to design those experiences to specific buyer segments. To do that, the most competitive and innovative retailers are using location intelligence, often fed by real-time data, to achieve a deep understanding of the customer decision-making process, gaining real-time insights into specific market activity, spikes in buying, competitor activities, or response to a new offer. These can include real estate trends, community-level demographics, purchasing mix, and any other behavior that has an inherently geographic context.

Providing a personalized shopping experience is not just about knowing what customers will want and where, but how they want it fulfilled. And the only way to do this is to study the demographics within each customer segment. With that knowledge, a retailer can configure end-to-end buying experiences for their customers and accelerate profitably into the world of empowered customers and unified commerce.

Learn how Location Intelligence can help digitally transform your organization.